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Erschienen in: Journal of Combinatorial Optimization 4/2022

28.06.2021

The enforcement of ECA regulations: inspection strategy for on-board fuel sampling

verfasst von: Lingyue Li, Suixiang Gao, Wenguo Yang

Erschienen in: Journal of Combinatorial Optimization | Ausgabe 4/2022

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Abstract

At present, the effective implementation of emission control areas regulation is faced with the problems of limited inspection capacity and unknown ship behavior. To bridge this gap, this paper quantitatively analyzes the inspection strategy (which arriving ships are selected for inspection) for on-board fuel sampling considering limited inspection capacity and ships’ violation behaviors. We first describe the behaviors of ships by considering economic benefit, social responsibility and other factors to analyze the actual situation. Based on this, a semi-random input model with limited inspection capacity is established and the optimal inspection strategy is obtained. Furthermore, the impacts of related factors on the optimal inspection strategy are analyzed. Finally, measures that based on automatic identification system data are proposed to improve the inspection strategy. The results show that compared to randomly select ships, the method proposed in our study can determine a more reasonable inspection strategy. Additionally, the AIS-based method may be a possible way to improve the inspection strategy.

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Fußnoten
1
According to the simulation, the numerator and denominator of c have the same order of magnitude. The range of c and \(\sigma\) are [0.6, 1.8] and 0.16, respectively. In addition, the determination of non-compliant ships is mainly affected by the relative value of b and has little relationship with the absolute value b. Therefore, the establishment of b is relatively reasonable.
 
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Metadaten
Titel
The enforcement of ECA regulations: inspection strategy for on-board fuel sampling
verfasst von
Lingyue Li
Suixiang Gao
Wenguo Yang
Publikationsdatum
28.06.2021
Verlag
Springer US
Erschienen in
Journal of Combinatorial Optimization / Ausgabe 4/2022
Print ISSN: 1382-6905
Elektronische ISSN: 1573-2886
DOI
https://doi.org/10.1007/s10878-021-00756-8

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